V. O. Zaloga, V. V. Nahornyi. Life prediction of cutting tools

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Citation: Zaloga, V. O., Nahornyi, V. V. (2014). Life prediction of cutting tools. Journal of Engineering Sciences, Vol. 1(3), pp. A1–A10.

The purpose of this article is to examine the methods of diagnosing the quality of functioning of techno-logical system of lathe. This article presents review of the results of mathematical modeling of the dynamics for the wear of a blade tool. It discusses the behavior of sound trend, which accompanying the cutting process as a source of indirect information about the state of the blade tool.

The development of a method begins from practice. It is known that when tool wear linear growth the trend of sound is sufficiently stable. When the tool wear is catastrophic the sound trend is fairly sharply.

The purpose of diagnosis is just the prediction of the moment of catastrophic tool wear. To solve this problem it is necessary to develop an appropriate prediction model. This model should be a function of time and includes seeking resource of the cutting tool. Under these conditions, the model will solve the basic problems of diagnostics in real time without interrupting the cutting process to monitor the status of the system and the quality of machined surface.

To solve this problem was developed predictive model, a distinctive feature and scientific novelty of which is that the seeking tool life is included in the model as one of its main parameters. This parameter is under of identification of the model parameters on the results of monitoring the sound accompanying the cutting process.

A tool life characterizes the deadline for its operation at which the tool should be replaced. Naturally, the cutting process must be suspended until the exhaustion of the tool life for to maintain the quality of workpiece.

For practical application of this method a “Hardware – software system”, which allows to diagnose the quality of the functioning of the metalworking technology system in real time was developed.

[restab title=”Key words”]control, diagnosis, prognosis, quality, forecast operating time.[/restab]
[restab title=”References”]

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